102 citations as recorded by crossref.

1. Rainfall intensity–duration thresholds for the initiation of landslides in Zhejiang Province, China T. Ma et al. https://doi.org/10.1016/j.geomorph.2015.05.016
2. Susceptibility Assessments of Landslides in Hulu Kelang Area Using a Geographic Information System-Based Prediction Model S. Jeong et al. https://doi.org/10.3390/su10082941
3. Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy) V. Tofani et al. https://doi.org/10.1007/s10346-017-0809-8
4. A process-based model for the definition of hydrological alert systems in landslide risk mitigation M. Floris et al. https://doi.org/10.5194/nhess-12-3343-2012
5. Influence of soil mechanical and hydraulic parameters on the definition of rainfall intensity and duration thresholds based on Transient rainfall infiltration and grid-based regional slope-stability model (TRIGRS) S. Zhang et al. https://doi.org/10.3389/feart.2022.971655
6. Predictive Power Evaluation of a Physically Based Model for Shallow Landslides in the Area of Oltrepò Pavese, Northern Italy R. Valentino et al. https://doi.org/10.1007/s10706-014-9758-3
7. Landslide displacement prediction based on multi-source data fusion and sensitivity states Y. Liu et al. https://doi.org/10.1016/j.enggeo.2020.105608
8. MAT.TRIGRS (V1.0): A new open-source tool for predicting spatiotemporal distribution of rainfall-induced landslides S. Ma et al. https://doi.org/10.1016/j.nhres.2021.11.001
9. Assessment of Landslide Susceptibility of the Wiśnickie Foothills Mts. (The Flysch Carpathians, Poland) Using Selected Machine Learning Algorithms T. Zydroń et al. https://doi.org/10.3389/feart.2022.872192
10. A simplified semi-quantitative procedure based on the SLIP model for landslide risk assessment: the case study of Gioiosa Marea (Sicily, Italy) M. Gatto et al. https://doi.org/10.1007/s10346-023-02040-8
11. Probabilistic failure analysis of infinite slopes under random rainfall processes and spatially variable soil J. Yuan et al. https://doi.org/10.1080/17499518.2018.1489059
12. Landslide hazard assessment: recent trends and techniques S. Pardeshi et al. https://doi.org/10.1186/2193-1801-2-523
13. Evaluation of the influence of soil mechanical parameters on the position of rainfall thresholds for shallow landslides M. Velásquez & R. Marin https://doi.org/10.1007/s12517-022-10859-z
14. Are real-world shallow landslides reproducible by physically-based models? Four test cases in the Laternser valley, Vorarlberg (Austria) T. Zieher et al. https://doi.org/10.1007/s10346-017-0840-9
15. A Watershed-Based Debris Flow Early Warning System Using Sensor Web Enabling Techniques in Heterogeneous Environments J. Chiu et al. https://doi.org/10.1109/JSTARS.2011.2181826
16. Assessment of Landslide Susceptibility of Physically Based Model Considering Characteristics of the Unsaturated Soil J. Kim & H. Park https://doi.org/10.9719/EEG.2014.47.1.49
17. Modeling the spatial occurrence of shallow landslides triggered by typhoons K. Chang et al. https://doi.org/10.1016/j.geomorph.2013.11.020
18. Soil Water Content Estimated by Support Vector Machine for the Assessment of Shallow Landslides Triggering: the Role of Antecedent Meteorological Conditions M. Bordoni et al. https://doi.org/10.1007/s10666-017-9586-y
19. Effect of Digital Elevation Model Resolution on Shallow Landslide Modeling Using TRIGRS T. Viet et al. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000233
20. Improving the reliability of landslide susceptibility mapping through spatial uncertainty analysis: a case study of Al Hoceima, Northern Morocco H. Rahali https://doi.org/10.1080/10106049.2017.1357767
21. Landslide prediction, monitoring and early warning: a concise review of state-of-the-art B. Chae et al. https://doi.org/10.1007/s12303-017-0034-4
22. Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations F. van Zadelhoff et al. https://doi.org/10.5194/nhess-22-2611-2022
23. The role of plants in the prevention of soil-slip: the G-SLIP model and its application on territorial scale through G-XSLIP platform L. Montrasio et al. https://doi.org/10.1007/s10346-023-02031-9
24. Survey of spatial and temporal landslide prediction methods and techniques https://doi.org/10.7744/kjoas.20160053
25. Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides J. Zhang et al. https://doi.org/10.3390/rs14225743
26. A Quantitative Analysis Method of Regional Rainfall-Induced Landslide Deformation Response Variation Based on a Time-Domain Correlation Model T. Wu et al. https://doi.org/10.3390/land11050703
27. Experimental study on the deformation and failure of a cut slope under rainfall J. Gan et al. https://doi.org/10.1007/s12665-025-12102-w
28. Landslide susceptibility assessment by TRIGRS in a frequently affected shallow instability area M. Ciurleo et al. https://doi.org/10.1007/s10346-018-1072-3
29. Adaptive neuro-fuzzy inference system (ANFIS) modeling for landslide susceptibility assessment in a Mediterranean hilly area C. Polykretis et al. https://doi.org/10.1007/s10064-017-1125-1
30. Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm H. Cui et al. https://doi.org/10.1007/s10346-024-02226-8
31. Investigating the Reliability of Stationary Design Rainfall in a Mediterranean Region under a Changing Climate D. Treppiedi et al. https://doi.org/10.3390/w15122245
32. A dynamic landslide hazard assessment system for Central America and Hispaniola D. Kirschbaum et al. https://doi.org/10.5194/nhess-15-2257-2015
33. Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview Z. Yang et al. https://doi.org/10.1080/17538947.2023.2229797
34. Incorporating Rainfall Forecast Data in X-SLIP Platform to Predict the Triggering of Rainfall-Induced Shallow Landslides in Real Time M. Gatto https://doi.org/10.3390/geosciences13070215
35. A novel approach for the computation of soil slope stability in distributed hydrologic applications R. Bonomelli et al. https://doi.org/10.1002/esp.70122
36. Physically-based landslide susceptibility analysis using Monte Carlo simulation in a tropical mountain basin R. Marin & Á. Mattos https://doi.org/10.1080/17499518.2019.1633582
37. An integrated approach to the study of catastrophic debris-flows: geological hazard and human influence C. Del Ventisette et al. https://doi.org/10.5194/nhess-12-2907-2012
38. Application of a process-based shallow landslide hazard model over a broad area in Central Italy E. Gioia et al. https://doi.org/10.1007/s10346-015-0670-6
39. A Statistical Mobilization Criterion for Debris-flow S. Yoon et al. https://doi.org/10.7843/kgs.2015.31.6.59
40. Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study L. Schilirò et al. https://doi.org/10.1016/j.scitotenv.2016.06.124
41. Evaluation and Prediction of Landslide Susceptibility in Yichang Section of Yangtze River Basin Based on Integrated Deep Learning Algorithm L. Chang et al. https://doi.org/10.3390/rs14112717
42. Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models C. Polykretis & C. Chalkias https://doi.org/10.1007/s11069-018-3299-7
43. A multi-objective physics-informed machine learning framework for landslide susceptibility mapping H. Cui et al. https://doi.org/10.1080/17499518.2026.2653043
44. Rapid prediction of rainfall-induced landslides over a wide area aided by a simulation-based surrogate model K. Tozato et al. https://doi.org/10.1016/j.compgeo.2025.107480
45. Hazard Mapping of Rainfall-induced Shallow Landslide in Phetchabun, Thailand K. ONO et al. https://doi.org/10.2208/jscejer.68.I_273
46. Dynamic Hazard Assessment of Rainfall-Induced Landslides Using Gradient Boosting Decision Tree with Google Earth Engine in Three Gorges Reservoir Area, China K. Yang et al. https://doi.org/10.3390/w16121638
47. GIS-based prediction method of landslide susceptibility using a rainfall infiltration-groundwater flow model J. Kim et al. https://doi.org/10.1016/j.enggeo.2014.09.001
48. Physical and numerical modelling of shallow landslides L. Montrasio et al. https://doi.org/10.1007/s10346-015-0642-x
49. Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides T. Tran et al. https://doi.org/10.1007/s12665-017-6635-4
50. Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event D. Park et al. https://doi.org/10.5194/nhess-13-2833-2013
51. The Dynamic Change and Effect of Rainfall Induced Groundwater Flow Y. He et al. https://doi.org/10.3390/w13192625
52. State fusion entropy for continuous and site-specific analysis of landslide stability changing regularities Y. Liu et al. https://doi.org/10.5194/nhess-18-1187-2018
53. Assessing two methods of defining rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains R. Marin et al. https://doi.org/10.1016/j.catena.2021.105563
54. Space-time prediction of rainfall-induced shallow landslides through Artificial Neural Networks in comparison with the SLIP model M. Gatto et al. https://doi.org/10.1016/j.enggeo.2024.107822
55. Derivation of Landslide Rainfall Thresholds by Geostatistical Methods in Southwest China Z. Xu et al. https://doi.org/10.3390/su16104044
56. Assessing probability of failure of urban landslides through rapid characterization of soil properties and vegetation distribution S. Fiolleau et al. https://doi.org/10.1016/j.geomorph.2022.108560
57. Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall N. Dolojan et al. https://doi.org/10.1016/j.enggeo.2023.107184
58. Rainfall infiltration and slope stability of alpine colluvial terraces subject to storms (NE Italy) P. Paronuzzi & A. Bolla https://doi.org/10.1016/j.enggeo.2023.107199
59. Slope susceptibility map for preventive measures against rainfall-induced slope failure H. Rahardjo et al. https://doi.org/10.1007/s44285-023-00006-9
60. Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy D. Zizioli et al. https://doi.org/10.5194/nhess-13-559-2013
61. A review on spatial, temporal and magnitude prediction of landslide hazard A. Tyagi et al. https://doi.org/10.1016/j.jaesx.2022.100099
62. Rainfall-induced shallow landslides triggered after vegetation removed because of fires: G-XSLIP application to Gioiosa Marea (Sicily, Italy) M. Gatto et al. https://doi.org/10.1051/e3sconf/202341504005
63. Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling G. Bicocchi et al. https://doi.org/10.1007/s10064-018-01449-z
64. Learning in an interactive simulation tool against landslide risks: the role of strength and availability of experiential feedback P. Chaturvedi et al. https://doi.org/10.5194/nhess-18-1599-2018
65. Deterministic approach for susceptibility assessment of shallow debris slide in the Darjeeling Himalayas, India S. Sarkar et al. https://doi.org/10.1016/j.catena.2016.02.009
66. A Multi-objective Polynomial Regression Approach for Evaluating Unsaturated Soil Slope Stability C. de Resende et al. https://doi.org/10.1016/j.apm.2026.117142
67. A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy L. Montrasio et al. https://doi.org/10.1007/s11069-014-1239-8
68. X-SLIP: A SLIP-based multi-approach algorithm to predict the spatial–temporal triggering of rainfall-induced shallow landslides over large areas M. Placido Antonio Gatto & L. Montrasio https://doi.org/10.1016/j.compgeo.2022.105175
69. A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. https://doi.org/10.1016/j.heliyon.2023.e23247
70. A comparison of statistical and deterministic methods for shallow landslide susceptibility zoning in clayey soils M. Ciurleo et al. https://doi.org/10.1016/j.enggeo.2017.04.023
71. Effect of Rainfall Intensity on Landslide Initiation: Flume Tests and Numerical Analysis Q. Tang et al. https://doi.org/10.3390/geotechnics3010007
72. Hydrological factors affecting rainfall-induced shallow landslides: From the field monitoring to a simplified slope stability analysis M. Bordoni et al. https://doi.org/10.1016/j.enggeo.2015.04.006
73. A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network H. Cui et al. https://doi.org/10.1016/j.jrmge.2024.08.005
74. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale S. Zhang et al. https://doi.org/10.5194/nhess-18-969-2018
75. Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting D. Lagomarsino et al. https://doi.org/10.5194/nhess-15-2413-2015
76. Ensemble learning for landslide susceptibility mapping: a review of machine learning and hybrid approaches H. Jiang et al. https://doi.org/10.1007/s13146-025-01221-x
77. Predicción de zonas susceptible a los procesos de remoción masa aplicando el modelo matemático red neuronal artificial en la localidad de Guatapurí y Chemesquemena, Colombia J. Estrada-Romero et al. https://doi.org/10.18273/revuin.v23n4-2024006
78. Improving Slope Stability Estimates by Incorporating Geophysical and Remote Sensing Monitoring Data into Hydro-Geomechanical Modeling S. Fiolleau et al. https://doi.org/10.2139/ssrn.4055920
79. On the Use of MATLAB to Import and Manipulate Geographic Data: A Tool for Landslide Susceptibility Assessment M. Gatto et al. https://doi.org/10.3390/geographies2020022
80. Development of time-variant landslide-prediction software considering three-dimensional subsurface unsaturated flow H. An et al. https://doi.org/10.1016/j.envsoft.2016.08.009
81. Physically based modelling techniques for landslide susceptibility analysis: A comparison V. Meena et al. https://doi.org/10.1088/1755-1315/1032/1/012033
82. Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources K. An et al. https://doi.org/10.3390/su10020293
83. Rainfall-induced landslide risk: the state of the art and future needs T. Wang et al. https://doi.org/10.1007/s12665-025-12541-5
84. Influence of hydraulic properties on physically modelling slope stability and the definition of rainfall thresholds for shallow landslides R. Marin & M. Velásquez https://doi.org/10.1016/j.geomorph.2019.106976
85. Assessing landslide susceptibility mapping in the Sikkim Himalayas using an ensemble machine learning approach I. Poddar & R. Roy https://doi.org/10.1007/s44288-025-00375-4
86. Understanding shallow landslides in Campos do Jordão municipality – Brazil: disentangling the anthropic effects from natural causes in the disaster of 2000 R. Mendes et al. https://doi.org/10.5194/nhess-18-15-2018
87. Interpreting the formation mechanism of a complex landslide: a case study of a reactivated landslide of a reinforced embankment slope Q. Huang et al. https://doi.org/10.1007/s10064-023-03492-x
88. Modelling Rainfall-induced Shallow Landslides at Different Scales Using SLIP - Part II L. Montrasio & R. Valentino https://doi.org/10.1016/j.proeng.2016.08.476
89. Experimentación reducida-controlada in situ del deslizamiento de suelo por efecto de flujo subsuperficial de agua E. Teófilo Salvador et al. https://doi.org/10.22201/fi.25940732e.2019.20n3.026
90. Assessment of rainfall-induced landslide susceptibility at the regional scale using a physically based model and fuzzy-based Monte Carlo simulation H. Park et al. https://doi.org/10.1007/s10346-018-01125-z
91. Prediction of Shallow Rainfall-Induced Landslides Using Shear Strength of Unsaturated Soil S. Ravindran & I. Gratchev https://doi.org/10.1007/s40098-020-00468-6
92. Physically based and distributed rainfall intensity and duration thresholds for shallow landslides R. Marin https://doi.org/10.1007/s10346-020-01481-9
93. Influence of subsurface flow by Lidar DEMs and physical soil strength considering a simple hydrologic concept for shallow landslide instability mapping S. Kim et al. https://doi.org/10.1016/j.catena.2019.104137
94. Assessment of sudden sediment source areas incurred by extreme rainfall in a mountainous environment: Approach using a subsurface hydrologic concept M. Kim et al. https://doi.org/10.1016/j.quaint.2018.10.031
95. Estimation of Rainfall-Induced Landslides Using the TRIGRS Model A. Dikshit et al. https://doi.org/10.1007/s41748-019-00125-w
96. Mapping method of rainfall-induced landslide hazards by infiltration and slope stability analysis N. Dolojan et al. https://doi.org/10.1007/s10346-020-01617-x
97. Developing Real-Time Nowcasting System for Regional Landslide Hazard Assessment under Extreme Rainfall Events Y. Deng et al. https://doi.org/10.3390/w13050732
98. Assessment of rainfall-induced shallow landslides in Phetchabun and Krabi provinces, Thailand K. Ono et al. https://doi.org/10.1007/s11069-014-1292-3
99. Understanding the sensitivity to the soil properties and rainfall conditions of two physically-based slope stability models R. Marin et al. https://doi.org/10.18273/revbol.v44n1-2022004
100. A comparative study of landslide susceptibility mapping using landslide susceptibility index and artificial neural networks in the Krios River and Krathis River catchments (northern Peloponnesus, Greece) C. Polykretis et al. https://doi.org/10.1007/s10064-014-0607-7
101. Modeling shallow landslides and root reinforcement: A review I. Murgia et al. https://doi.org/10.1016/j.ecoleng.2022.106671
102. Limit equilibrium method-based 3D slope stability analysis for wide area considering influence of rainfall K. Tozato et al. https://doi.org/10.1016/j.enggeo.2022.106808